Automated AXIS Data Quality Exception Alerts
Every morning during data intake, WebRun opens AXIS to run its data validation checks against the incoming policy, claims, and asset extracts, logs every exception, a missing field, an out-of-range value, or a duplicate record, as an Asana task assigned to the data owner, and posts a Slack alert with the count.
How do I catch data quality exceptions before a model run?
Every morning during data intake, WebRun runs AXIS's data validation checks against incoming policy, claims, and asset extracts, and logs every exception, a missing field, an out-of-range value, or a duplicate record, as an Asana task assigned to the data owner. It posts a Slack alert with the count, so bad data never quietly reaches a model run.
- Data exceptions are caught and assigned before the model run starts, not after
- Every exception is an owned Asana task instead of a line in a log file
- Blocking issues are called out clearly so no run starts on bad data by accident
Built for valuation actuaries · actuarial data teams · actuarial consulting firms · model governance teams
What does WebRun do on every run?
The exact actions WebRun takes, in order - in plain language, so you can adjust anything.
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WebRun signs in and gets to work
Opens
www.moodysanalytics.comin a real browser with your saved login - no setup, no API keys. -
1
Moody's Analytics AXIS - run the data validation checks
moodysanalytics.com
WebRun opens Moody's Analytics AXIS to run the data validation checks. - Open AXIS and run the data validation checks against the incoming policy, claims, and asset extracts
- Capture each exception, missing field, out-of-range value, or duplicate record, and which source file it came from
- Note whether any exception is severe enough to block the run
Done when Every validation exception from today's data load is captured with its source and severity.
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2
Asana - log each exception as a task
- Open the Data Quality Exceptions project
- Create a task for each exception naming the field, the source file, and the severity
- Assign each task to the data owner responsible for that source
Done when Every exception has an assigned Asana task.
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3
Slack - alert on the exception count
slack.com
WebRun opens Slack to alert on the exception count. - Post the actuarial team the total exception count and how many are severe enough to block the run
- List the data owners with open exceptions
- Note that the model run should not proceed until blocking exceptions clear
Done when The team has today's exception count and blocking status in Slack.
How is each run configured?
Secure by default
Connect once, stays signed in
WebRun signs in once and keeps each session in a persistent environment, so every run picks up right where it left off.
Every action is checked against this policy before it runs.
Questions, answered
Will it fix or override any bad data itself?
No. WebRun only logs each exception as a task and alerts the team. Correcting a policy, claims, or asset record stays with the data owner. WebRun never edits source data or a model input.
Will it let a model run proceed with bad data?
It does not control the run itself, it only flags which exceptions are severe enough to block one. Whether to proceed, wait, or exclude a record is a decision your actuarial team makes.
How does it decide what counts as an exception?
It uses the validation checks already configured in AXIS, missing fields, out-of-range values, and duplicate records, so the exceptions reported match exactly what your model would have flagged on its own.
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